With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2010 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the north coast of Canada. The study areas include Beaufort Sea, Mackenzie Delta channels and Banks Island in the western Canadian Arctic and James Bay, Hudson Bay, Nunavik, Resolute Bay, Victoria Strait, Baffin Island and Coronation Gulf in the eastern Canadian Arctic. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset (excluding Nunavik) to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2010 to 2016, within the 8 study sites, about 16,800 km of shoreline were segmented.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2013 and 2019, georeferenced high-definition videography and photos were collected for various study sites along the west coast. The study areas include the mainland, inlets, channels and islands along the BC coast starting from Kitimat in the north to Quadra Island in the south, including Haida Gwaii and North Vancouver Island in the west and Burrard Inlet in the extreme south. Data was collected during low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each of the study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground samples (when available) and a second interpreter QA (quality analysis) was performed on the dataset to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres (45 metres for study areas surveyed in 2018-19) to 2500 metres. In total, from 2013 to 2019, about 15,000 km of shoreline were segmented.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past few decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e., Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2011 and 2016, georeferenced high-definition videography and photos were collected for various study sites along the east coast. The study areas include Labrador, Bay of Fundy and Chedabucto Bay in Atlantic Canada. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e., shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground observations (when available) and a second interpreter QA (quality analysis) was performed on each dataset to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 metres to 2500 metres. In total, from 2011 to 2016, within the 3 study sites, about 1,850 km of shoreline were mapped.

With the changing climate conditions, marine traffic along Canada’s coastal regions has increased over the past couple of decades and the need to improve our state of preparedness for oil-spill-related emergencies is critical. Baseline coastal information, such as shoreline form, substrate, and vegetation type, is required for prioritizing operations, coordinating onsite spill response activities (i.e. Shoreline Cleanup Assessment Technique [SCAT]), and providing information for wildlife and ecosystem management. Between 2010 and 2019, georeferenced high-definition videography and photos were collected for various study sites across coastal Canada. The study areas include Beaufort Sea, Mackenzie Delta channels and Banks Island in the western Canadian Arctic; James Bay, Hudson Bay, Nunavik, Resolute Bay, Victoria Strait, Baffin Island and Coronation Gulf in the eastern Canadian Arctic; Labrador, Bay of Fundy and Chedabucto Bay in Atlantic Canada and Kitimat, Haida Gwaii, North Vancouver Island, Mainland BC and Burrard Inlet in the northern Pacific. Data was collected during ice-free and low tide conditions (where applicable) between July and September. Low-altitude helicopter surveys were conducted at each study site to capture video of the shoreline characteristics. In addition to acquiring videography, ground-based observations were recorded in several locations for validation. Shoreline segmentation was then carried out by manual interpretation of the oblique videography and the photos aided by ancillary data. This involved splitting and classifying the shoreline vectors based on homogeneity of the upper intertidal zone. Detailed geomorphological information (i.e. shoreline type, substrate, slope, height, accessibility etc.) describing the upper intertidal, lower intertidal, supratidal and backshore zones was extracted from the video and entered into a geospatial database using a customized data collection form. In addition, biological characteristics like biobands, water features, fauna, human use etc. observed along the coast were recorded. The data was also validated through ground samples (when available) and a second interpreter QA (quality analysis) was performed on each dataset (excluding Nunavik) to ensure high quality and consistency. The final dataset contains segments ranging in length from 150 m to 2500 m (except Nunavik). The minimum segment length is 45 m for study areas in the west coast that were surveyed in 2018-2019. In total, about 33,700 km of shoreline were segmented within all the survey zones.

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.

The Coastal Ice Ocean Prediction System (CIOPS) provides a 48 hour ocean and ice forecast over different domains (East, West, Salish Sea) four times a day at 1/36° resolution. A pseudo-analysis component is forced at the ocean boundaries by the Regional Ice Ocean Prediction System (RIOPS) forecasts and spectrally nudged to the RIOPS solution in the deep ocean. Fields from the pseudo-analysis are used to initialize the 00Z forecast, whilst the 06, 12 and 18Z forecasts use a restart files saved at hour 6 from the previous forecast. The atmospheric fluxes for both the pseudo-analysis and forecast components are provided by the High Resolution Deterministic Prediction System (HRDPS) blended both spatially and temporally with either the Global Deterministic Prediction System (GDPS) (for CIOPS-East) or an uncoupled component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution (for CIOPS-West) for areas not covered by the HRDPS.